smog (version 2.1.0)

sim_rct_biomarker: Simulate a randomized clinical trial with biomarkers

Description

sim_rct_biomarker is used to simulate clinical trial data with specified treatment, prognostic, and predictive effect sizes.

Usage

sim_rct_biomarker(n = 50, p = 100, p_prog = 5, p_pred = 5,
  p_both = 5, v_trt = 0.4, v_prog = 0.2, v_pred = 0.2,
  v_err = 0.2, corr = NULL, family = "gaussian", ...)

Arguments

n

Number of subjects.

p

Number of biomarkers.

p_prog

Number of biomarkers with prognostic effects only.

p_pred

Number of biomarkers with predictive effects only.

p_both

Number of biomarkers with both prognostic and predictive effects

v_trt

Variance of response due to treatment.

v_prog

Variance of response due to prognostic effects.

v_pred

Variance of response due to predictive effects.

v_err

Variance of response due to random noise.

corr

Autocorrelation parameter between biomarkers, default is NULL.

family

The distribution family for response variable, can be gaussian'', or binomial''. Default is ``gaussian''.

...

further arguments passed to or from other methods.

Value

A list containing several variables.

T

Treatment status in 1 or -1 values.

X

Biomarkers.

W

Hadamard product of treatment and biomarkers.

M

Model matrix - binding of T, X, and W.

Y

Response.

Y0

Response without error.

tau

Treatment effect.

beta

Prognostic effects.

gamma

Predictive effects.

theta

All effects corresponding to M.

References

ma2019structuralsmog

Examples

# NOT RUN {
sim <- sim_rct_biomarker(n = 1e3)
var(as.vector(sim$T * sim$tau))
var(as.vector(sim$X %*% sim$beta))
var(as.vector(sim$W %*% sim$gamma))

# }